Multicarrier modulation

ABSTRACT

Signals are transmitted on sub-channels at different but mutually overlapping frequencies. A receiver separates the sub-channels into component signals Z 0  . . . C 254  Prior to decoding ( 7 ), interference estimates C 0  . . . C 254  are subtracted from the components. These estimates are deduced from the signals received on the idle sub-channels (or on sub-channels from which a known or estimated signal is subtracted), for example by calculating ( 10 ) parameters defining a model of the interference and using these ( 11 ) to generate the interference estimates.

This application is the US national phase of international applicationPCT/GB02/05501 filed 5 Dec. 2002 which designated the U.S. and claimsbenefit of EP 01310258.7, dated 7 Dec. 2001, the entire content of whichis hereby incorporated by reference.

FIELD OF TECHNOLOGY

This application is concerned with multicarrier modulation techniques,which serve to transport information over a communications channel bymodulating the information on a number of carriers, typically known assub-channels.

BACKGROUND AND SUMMARY

Of particular interest are discrete systems where, rather thanmodulating a carrier with a continuously variable information signal,successive time periods (“symbols”) of the carrier each serve totransmit one piece of information; that, is, the modulated informationdoes not vary during the course of a symbol.

Of the most practical interest is the situation where the information tobe sent is in digital form, so that each symbol serves to transport anumber of bits, but this is not in principle necessary and sampledanalogue signal could be sent i.e. the information signal is quantisedin time but may or may not be quantised in amplitude.

Quadrature modulation may if desired be used, where both the phase andamplitude of the carrier are varied, or (which amounts to the samething) two carriers at the same frequency but in phase quadrature mayeach be modulated independently. A “multicarrier symbol” may thusconsist of a time period during which are transmitted (say) 256 carriersat different frequencies plus 256 carriers at the same set offrequencies but in phase quadrature. For digital transmission, up to 512groups of bits may be modulated onto these carriers. Normally thecarriers are harmonically related, being integer multiples of the symbolrate (though in systems using a “cyclic prefix” the symbol rate isslightly lower than this statement implies). This form of modulation isparticularly attractive for use on poor quality transmission paths,since the number of bits allocated to each carrier can be tailored tothe characteristics of the path, and indeed carriers may be omitted inparts of the frequency spectrum in which quality is especially poor.

The number of bits sent on each sub-channel may if desired be varieddepending on the signal and noise levels in each sub-channel. This canbe a particular advantage for transmission paths which suffer crosstalkor radio frequency interference, since the system can adaptautomatically to avoid regions of frequency spectrum that are unsuitablefor data transmission. The number of bits sent on each sub-channel mayif desired be varied adaptively depending on the signal and noise levelsin each sub-channel as observed from time to time. This can be aparticular advantage for transmission paths which vary significantlyover the course of a communication.

Multicarrier modulation has been standardised for use on copper pairlinks in a form known as discrete multitone (DMT) modulation. This isdescribed in an ANSI standard (T1.413-1998) for asymmetrical digitalsubscriber loop technology and also a European standard [DTR/TM-03050]and an international standard [ITU G.adsl].

A modulator for multicarrier systems may be constructed with a bank ofoscillators at the respective frequencies, each followed by a modulator,whilst a receiver might consist of a bank of synchronous demodulatorseach driven by an oscillator synchronised to the correspondingoscillator at the transmitting end. In practice, however, a more popularapproach is to regard the data values to be transmitted for a givensymbol as Fourier coefficients and to generate the modulated signal bymeans of an inverse Fourier transform. Similarly the demodulator wouldapply a Fourier transform to the received signal in order to recover thetransmitted carrier phase and amplitude (or in-phase and quadraturecomponents) which can then be decoded using standard quadratureamplitude modulation (QAM) techniques. Such a demodulator, as envisagedby the above-mentioned ANSI standard, is shown in FIG. 1. The receivedsignal is filtered by a filter 1, and converted into digital form in ananalogue- to digital converter 2. The digitised samples are entered intoa buffer 3, synchronisation being provided by a control unit 4 so that,for each symbol, a block of 512 samples is assembled in the buffer.These are then supplied to a discrete Fourier transform unit 5 whichprocesses the samples to recover complex values z_(j)(j=0 . . . 254)representing the transmitted carrier (plus of course, noise), output asin-phase and quadrature components l_(j), Q_(j)(that is,z_(j)=l_(j)+iQ_(j)). These are scaled at 6, each z_(j) being multipliedby a complex number to compensate for delay and attenuation suffered bythe relevant carrier, and then fed to a QAM decoder 7 (usually employingsome form of convolutional code and a soft-decision decoder), wherebythe desired data values are recovered.

One of the functions of the control unit 4, in addition tosynchronisation, is to engage, at start-up, in a training sequence, thatis, a dialogue with the transmitting modulator in which it obtains theinformation it needs about the transmitted signal, for example, whichsub-channels are actually in use, how many bits are carried by eachsub-channel, and what QAM constellations are being used by themodulator. In some systems, these parameters may be changed dynamicallyby further negotiation between the two ends during actual transmission.It is noted that the timing output from the control unit 4 serves forsynchronisation of the various parts, whilst the control outputindicates which sub-channels, and which constellations, are currently inuse.

The invention is defined in the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Some embodiments of the invention will now be described, by way ofexample, with reference to the accompanying drawings, in which:

FIG. 1 is a block diagram of a known form of receiver;

FIG. 2 is a block diagram of one example of receiver according to theinvention;

FIG. 3 is a block diagram of another example of receiver according tothe invention; and

FIGS. 4 and 5 show details of parts of the receiver of FIG. 3; and

FIG. 6 is a graph showing the performance of one version of theinvention.

DETAILED DESCRIPTION

The general aim of the receiver now to be described is based on theobservation that, where a sub-channel has, owing to the presence ofinterference, been taken out of use, the signals received on thatsub-channel will consist only of some component of the interferingsignal, along with additive white Gaussian noise. Consequently it aimsto deduce from the signals received on the idle sub-channel someknowledge about the nature of the interfering signal and use thisknowledge to apply a correction to the signals received on the othersub-channels. Sub-channels in which the transmitted signal is known(e.g. pilot tones) can also be used in the same way if the knowncomponent is firstly subtracted. Sub-channels carrying data can also beused in the same way if the signal component is firstly estimated andsubtracted.

Thus the receiver shown in FIG. 2 has the same general structure as thatof FIG. 1 but additionally has interference cancellation units 10, 11which receive the values z_(j) from the DFT unit 5, and information fromthe control unit 4 indicating which sub-channels are idle. Theycalculate corrections c_(j) to be made and subtract these from the z_(j)values in subtractors S_(j) to form corrected values z_(j)′ which aresupplied to the scaling unit 6 and further processed as alreadydescribed.

Of course, the idea that the received signal on an idle sub-channel canallow one to infer something about the interference on some othersub-channel implies a correlation between the interference on the twochannels. It follow that it is not possible to compensate for true whitenoise. Conceptually, at least, the idea involves the notion of a modelof the interfering signal. The simplest such model is a pure sinusoidwhich is completely characterised by three real numbers, the mostnatural choice being its frequency F, phase φ and amplitude A:f(t)=A·cos(2πFt+φ)  (1)

This could for example represent the constant carrier portion of ingressfrom an AM radio transmitter. In case it should be supposed that such asinusoid would affect only one sub-channel, it is pointed out that, inpractice, the sub-channels occupy overlapping portions of frequencyspectrum. Such a sinusoid will affect all sub-channels to some extent,unless its frequency is exactly the carrier frequency of one sub-channel(in which special case it affects only that one sub-channel).

An example of a more complex model might be one where the interferingsignal is the sum of two or more such sinusoids.

Taking this model as an example, the cancellation comprises thefollowing steps:

-   -   (a) determine the expected contribution of the assumed        interfering signal to the received signal z_(j) in the idle        sub-channels;    -   (b) compare these with the actual signals z_(j) in respect of        the idle sub-channels to estimate values for the model        parameters;    -   (c) use these parameters to calculate the contributions c_(j) of        the assumed interference in the sub-channels actually in use;    -   (d) subtract c_(j) from the z_(j) values.

Steps (a) and (b) are performed by the parameter estimation unit 10,which is connected to receive the values z_(j) from the DFT unit 5, andto the control unit 4 from which it receives signals indicating whichchannels are not in use. Such signals are of course present in aconventional decoder.

The expected signal z_(k)″ on sub-channel k due to the interferingsignal f(t) is simply the output that the DFT unit 5 would produce whensupplied with the signal f(t). In analytical form this is

$\begin{matrix}{z_{k}^{''} = {\frac{1}{\tau}{\int_{{- \tau}/2}^{\tau/2}{{{f(t)} \cdot {\exp( \frac{{- 2}{\mathbb{i}}\; k\;\pi\; t}{\tau} )}}{\mathbb{d}t}}}}} & (2)\end{matrix}$

Substituting for f(t) from Equation (1) and integrating, we obtain:

$\begin{matrix}{z_{k}^{''} = {\frac{A}{2}( ( {{{\exp( {{\mathbb{i}}\;\varphi} )}{{sinc}( {{\tau\; F} - k} )}} + {{\exp( {{- {\mathbb{i}}}\;\varphi} )}{{sinc}( {{\tau\; F} + k} )}}} ) }} & (3)\end{matrix}$where φ is the symbol period and the time origin t=0 corresponds to themiddle (or other fixed position) of the block used by the receiver.

The model parameters are estimated so as to minimise the error using aleast mean squares (LMS) approach, this error being the square of thedifference between the predicted signal and the actual one. We prefer tonormalise this by division by the time-average of the difference oversome recent time-period T:

$\begin{matrix}{e = \frac{\sum\limits_{k}{{z_{k}^{''} + p_{k} - z_{k}}}^{2}}{\frac{1}{T}{\sum\limits_{t}{{z_{k}^{''} + p_{k} - z_{k}}}^{2}}}} & (4)\end{matrix}$the summation being for all values of k corresponding to idlesub-channels, and where p_(k) is the known signal value (zero for idlesubchannels). e is then differentiated with respect to the modelparameters, to find those parameters which bring the derivatives tozero. Sometimes this can be performed analytically, using a programmedmethod, to solve it once for each symbol. However, better results may beachieved my making small adjustment over many symbol periods, forexample using the well-known “steepest descent” method, though any otherminimisation method can be used (e.g. the Widrow-Hoff method). Thus onetakes the parameters determined for the preceding symbol and adjuststhem to provide a reduction in the error e for the new symbol, butsubject to a limit on the amount by which the parameters are permittedto change, so that the estimate is gradually improved (and trackschanges in conditions) yet is not unduly affected by short-termvariations of a kind which cannot be modelled—for example in the case ofaudio signals modulated on a RF carrier, it would be relatively easy tomodel the carrier but rather more difficult to model the modulation.These limits should be selected on the basis of the expectedcharacteristics of the source of interference, so that for example aninterfering RF transmitter may be expected to have a stable frequency,thereby implying a small limit (and hence slow adaptation), whereas itsamplitude might vary and imply therefore a relatively large limit, sothat more rapid changes can be tracked. In practice this process can beimplemented using a suitably programmed digital signal processing (DSP)chip. Step (c) is performed by the model execution unit 11.

Here, the estimated contribution Cm of the interference model to thereceived z_(j) for the sub-channels in use is again the output that theDFT unit 5 would produce when supplied with the signal f(t) having theparameters just determined, and this can be calculated as indicatedabove or by using a DFT. Obviously there is no need to calculate c_(m)for the idle sub-channels. Also, the value of the information in a givenidle sub-channel in estimating corrections for an in-use sub-channeldiminishes the further away (in terms of frequency) the in-usesub-channel is from the idle sub-channel. Consequently one might chooseto reduce the amount of computation by omitting to calculate c_(m) forin-use sub-channels which are more than a certain number of channelsaway from the nearest idle sub-channel. Indeed this is desirable sinceapplying corrections for subchannels where interference either is absentor is uncorrelated with the information available in the idlesub-channels will produce no benefit and may be disadvantageous inincreasing the amount of Gaussian noise.

The above example assumes a single sinusoid model with three parameters,i.e. three degrees of freedom. It is necessary that the number of piecesof information used to estimate the parameters be at least equal to thisnumber, and preferably exceed it, in order to permit a reasonablyaccurate estimate to be made. It follows therefore that there must be atleast two idle sub-channels thereby providing two values z_(i) eachhaving in-phase and quadrature components. In practice as many as six orseven subcarriers may be turned off in the vicinity of interference,thus providing a substantial amount of information. More complex modelsmight of course be used: for example one might choose a model consistingof two (or more) sinusoids, provided that there is a sufficient numberof idle sub-channels.

The previous examples estimated the nature of the interference byreference to the signals received in the idle sub-channels. In amodified version one uses also

-   -   (a) signals received in sub-channels whose content is known, for        example a pilot tone. In this case the known content must be        subtracted from the signal before it can be used for estimating        the model.    -   (b) signals received in sub-channels carrying data, if the        sub-channel can be demodulated, and the effect of the data        subtracted.

An initial coarse estimate of where interferers are would be a usefulsource of initialisation for the model proper, speeding up initialconvergence a lot. For a multiple sinusoids model, if the real noisecomponents are in different parts of the band it is conceivable thatthey could be treated independently.

A possibility that may arise with the systems described is that theresulting improvement in error rate may make it possible thatsub-channels formerly rendered idle due to interference may becomeusable again. Conventional mechanisms as used for adaptive allocation ofsub-channels can be used. These involve the sending of test signals onthe idle sub-channel so that its current quality may be assessed. Wherethis occurs, the receiver, upon being warned of the impending testsignal, must (in idle-only correction) cease to monitor the sub-channelfor interference, or (otherwise) subtract the test signal before usingthe received signal for interference correction control. The sameapplied when the idle sub-channel ceases to be idle.

FIG. 3 shows another form of receiver, again with the same basicstructure as in FIG. 1. An interference cancellation unit 21 calculatescorrections c_(p) to be made, and these are subtracted in subtractorsS_(p) from the sub-channel values. In this instance the correctionoccurs after the scaling unit 5 so that the corrected value isa _(p) z _(p) −c _(p)  (5)where a_(p) is the relevant scale factor.

The correction c_(p) is a weighted sum of the scaled sub-channel valuesa_(p)z_(p) for the idle sub-channels.

$\begin{matrix}{c_{P} = {\sum\limits_{q}{a_{q}z_{q}w_{qp}}}} & (6)\end{matrix}$

If however it is desired to make use also of the predictable orestimable sub-channels, then the noise element of the receivedsub-channel is estimated asn _(q) =a _(q) z _(q)−θ_(q)  (7)where θ_(q) is the estimated data content for a data-carryingsub-channel—for example, in a QAM system, the (complex) coordinate ofthat point of the QAM constellation which has the smallest Euclideandistance from the (complex) value represented by a_(q)z_(q). This isindicated in FIG. 4 by a hard slicer 211. The same method may be usedfor determining θ_(q) for an idle or predictable sub-channel, but it isprobably preferable to force θ_(q) to zero (or the known expected value)in such cases.

It may be possible to use a soft decision in the slicer 211, on thelines of that taking place in the decoder 7, though probably this willgive small benefit at the expense of greater complexity.

Thus the correction becomes

$\begin{matrix}{c_{p} = {\sum\limits_{{{all}\mspace{11mu} q} \neq p}{n_{q}w_{qp}}}} & (8)\end{matrix}$

Computing the correction c_(p) using all the sub-channels q≠p (254 inthis example) is computationally onerous and, on the basis (as notedearlier) that the value of the received signals for correctiondiminishes the further infrequency one moves from sub-channel p, one mayprefer to use only a limited number within a range ±Δ, e.g.

$\begin{matrix}{c_{p} = {{\sum\limits_{q = {p - \Delta}}^{p - 1}{n_{q}w_{qp}}} + {\sum\limits_{q = {p + 1}}^{p + \Delta}{n_{q}w_{qp}}}}} & (9)\end{matrix}$(truncation at the limits is expressed by defining w_(qp)=0 for q<0 orq>254, though out-of-band information could also be made use of ifdesired.).

In a simple version of this system, the weighting factors w_(qp) maysimply be fixed. For example, a version obtaining a correction only fromone neighbouring sub-channel could use a weight of 1+i0.

We prefer, however to calculate the weighting factors taking intoaccount the characteristics of the signals actually received. One methodof doing this will now be described.

The weighting factors w_(pq) can be evaluated using the well-known“steepest descent” method. This procedure—which is the same whether allq≠p or only some values of q are used—is performed using error valuesfrom the decoder 7. This is a soft-decision decoder typically using aViterbi algorithm to decode convolutionally-coded data. The resultantdecision for a particular sub-channel p is denoted by x_(p) andillustrated by soft slicers 71. Note that x_(p) is the complexco-ordinate of the QAM constellation value, not the actual data. Anerror signal e_(p) is the difference between the input and thisdecision, that ise _(p) =a _(p) Z _(p) −c _(p) −x _(p)  (10)

This value is routinely produced for data and tone-bearing sub-channelsin real receivers as it also used for maintaining synchronisation: thusthe decoder 7 can be a conventional decoder. If e_(p) should be requiredfor an idle sub-channel (e.g. for calculating weights w_(pq) prior tobringing the sub-channel back into service) x_(p) can be forced to zero.

The calculation of the weighting factors is shown as performed in theunit 22. The aim is to minimise the average |e_(p)|². The followinganalysis works by considering |e_(p)|² as a function of all the realparameters (so the real and imaginary parts of w_(qp) are consideredseparately), estimating the direction of steepest descent, and taking asmall step downhill

$\begin{matrix}{{{Let}\mspace{14mu} w_{qp}} = {{u_{qp} + {{i \cdot v_{qp}}\mspace{14mu}{( {u,{{v\mspace{14mu}{{real}:i^{2}}} = {- 1}}} ).{So}}\mspace{14mu} e_{p}}} = {{a_{p}z_{p}} - {\sum\limits_{q}{n_{q}( {u_{qp} + {i \cdot v_{qp}}} )}} - x_{p}}}} & (11)\end{matrix}$

Ignoring for the moment the possibility of changes in x_(p) due to achange in w_(qp), we find

$\begin{matrix}{\mspace{20mu}{\frac{\partial e_{p}}{\partial u_{qp}} = {{{- n_{q}}\mspace{14mu}\frac{\partial e_{p}}{\partial v_{qp}}} = {- {in}_{q}}}}} & (12) \\{\frac{\partial{e_{p}}^{2}}{\partial u_{qp}} = {\frac{{\partial e_{p}} \cdot e_{p}^{*}}{\partial u_{qp}} = {{( {e_{p} \cdot ( {- n_{q}} )^{*}} ) + ( {( {- n_{q}} ) \cdot e_{p}^{*}} )} = {2\mspace{11mu}{Re}\{ {{- e_{p}} \cdot n_{q}^{*}} \}}}}} & (13) \\{\frac{\partial{e_{p}}^{2}}{\partial v_{qp}} = {\frac{{\partial e_{p}} \cdot e_{p}^{*}}{\partial u_{qp}} = {{( {e_{p} \cdot ( {{- i} \cdot n_{q}} )^{*}} ) + ( {( {{- i} \cdot n_{q}} ) \cdot e_{p}^{*}} )} = {2\mspace{11mu}{Im}\{ {{- e_{p}} \cdot n_{q}^{*}} \}}}}} & (14)\end{matrix}$

The direction of the steepest ascent is the vector of all the partialderivatives of |e_(p)|². Thus, for each symbol, an adjustment to theweights to be made so as to give an updated weight to be used for thenext symbol given byu _(qp)−μ·2Re{−e _(p) ·n _(q)*}  (15)v _(qp)−μ·2Im{−e _(p) ·n _(q)*}  (16)where μ is a small positive constant (<<1) which controls the rate oftraining and may be varied from time to time but at any given time thesame for all q, p.Or,w _(qp)(k)=w _(qp)(k−1)+2μ·e _(p)(k−1)·n _(q)*(k−1)  (17)where a(k) denotes the value of a for symbol k.

Thus the task of the unit 20 is simply to calculate (once for eachblock) 2μ·e_(p)·n_(q)*, add it to the current value of w_(qp), andsupply the new value of w_(qp) to the correction unit 21. At start-up,the initial value of w_(qp) can be set to zero (0+i0).

Recalling that we ignored x_(p) in the derivation of the weights, if anotional increment Δu_(qp) in u_(qp) (or similarly for v_(qp)) is suchas would cause a change in x_(p), there is a discontinuity in e_(p) andthe differential coefficient is incorrect, a fact which has beenignored. Another way of viewing this simplification is by noting thatthe adjustments to w_(qp) are such as would tend to pull the value ofa_(p)z_(p)−c_(p) closer to x_(p). If x_(p) is in fact wrong, thisadjustment can be in the wrong direction. However, provided x_(p) is notwrong too often, in practice w_(qp) nevertheless converges to anappropriate value. The method described is robust at error rates wellabove those normally considered acceptable for such systems.

Mention has already been made of the possibility of using fixed weights.A method of calculating weights for this version of the invention willnow be described. Unlike the preceding calculation, this method cannotrely on observed characteristics of signals recently received: rather,as discussed earlier in relation to FIG. 2, it relies on the notion of amodel of the interfering signal. It is in this sense that they arefixed. They can be calculated in advance, and provided to the receiveras a look-up table, or they could be calculated from time to time by thereceiver, to accommodate changes in the selection of which subchannelsare and are not in use.

In this example it is taken as given that a number of contiguoussub-channels are idle, and the postulated interference is white noise ofconstant power spectral density over a frequency range slightly narrowerthan that corresponding to the idle sub-channels. In one specificexample if sub-channels 54 to 61 inclusive are idle, and with guardbands of 1.6 subchahnels, the white noise would be of a constant powerover the frequency range corresponding to subchannels 55.5 to 60.1.

Suppose that the noise is n(f) and (hence) the noise power spectrum isN(f)=n²(f).

This representation is of course valid for any form of the postulatednoise.

The interference generated in subchannel k having centre frequency f_(k)is termed the susceptibility of subchannel k to the interference and isgiven by

$\begin{matrix}{S_{k} = \{ {\int_{- \infty}^{+ \infty}{{n(f)}{{sinc}( {f - f_{k}} )}{\mathbb{d}f}}} \}^{2}} & (18)\end{matrix}$

However, if (as here) the noise is uncorrelated, this can be simplifiedto

$\begin{matrix}{S_{k} = {\int_{- \infty}^{+ \infty}{{{N(f)}\lbrack {{sinc}( {f - f_{k}} )} \rbrack}^{2}{\mathbb{d}f}}}} & (19)\end{matrix}$

After subtraction, the susceptibility then becomes

$\begin{matrix}{S_{k} = {\int_{- \infty}^{+ \infty}{{{N(f)}\lbrack {{\sin\;{c( {f - f_{k}} )}} - {\sum{{w_{mk} \cdot \sin}\;{c( {f - f_{m}} )}}}} \rbrack}^{2}{\mathbb{d}f}}}} & (20)\end{matrix}$where w_(mk) are the weights, f_(m) is the centre frequency ofsub-channel m and the summation is performed for all idle subchannels mto be used.

The task of finding the weights is to find for each wanted subchannel kthe values of w_(km) that minimise S_(k). This can conveniently beaccomplished by using one of the standard minimisation methods, forexample the Fletcher-Reeves-Polak-Riviere method (this and other suchmethods are described in Presteukolsky, Vetterling and Flannery,“Numerical Recipes in C”, Cambridge University Press, 2^(nd) Edition,1992).

In a test, using the example figures given above for the postulatednoise, weights w for the five adjacent subchannels on each side of theidle ones (i.e. k=49 . . . 53 and 62 . . . 66) were calculated. It wasfound that the RFI immunity increased by around 30 dB at a cost ofincreased AWGN susceptibility of about 2 dB. In more detail, the effectsof the correction are shown in the following table.

AWGN bin RFI change change 49 −23.55 [dB] 0.99 [dB] 50 −25.06 [dB] 1.22[dB] 51 −27.00 [dB] 1.53 [dB] 52 −29.80 [dB] 1.96 [dB] 53 −34.96 [dB]2.52 [dB] 62 −26.24 [dB] 1.56 [dB] 63 −23.36 [dB] 1.15 [dB] 64 −21.98[dB] 0.89 [dB] 65 −21.07 [dB] 0.71 [dB] 66 −20.35 [dB] 0.58 [dB]

FIG. 6 is a graph showing the susceptibility of the ten correctedsubchannels, overplotted. Each bin has a main lobe roughly where itsuncorrected main lobe is, and sidelobes which fall away as 1/f² rathersimilar to the uncorrected subchannel, but with the sidelobes in thenoise band about 30 dB lower than the uncorrected subchannel.

By construction these subchannels are not affected by each others'legitimate signals; the legitimate output of the transmit end of the DMTlink only contributes into a subchannel from that subchannel's propersignal and the signals in the notch subchannels—which all have zerosignals.

It will of course be appreciated that a similar analysis could beperformed for noise occurring in more than one idle channel region, orindeed at the regions bordering the band edges.

It should be observed that the slicers, multipliers and subtractorsshown in units 10, 11, 20, 22 in the drawings are largely schematic:although the receivers could be built this way, we prefer to implementthe processes we describe using a suitable programmed digital signalprocessing (DSP) chip. Although these units could be implemented asindividual such chips, a single one could be used: indeed if desired asingle DSP could be used to implement these functions along with theconventional signal processing required of such a receiver, includingthe FFT calculations, the equalization, the quantisation, the trelliscode decoding and the synchronisation processes which keep the receiverin step with the transmitter. The same device may also be executing thedialogue with the transmitter about bit reallocation and so on.

1. A method of receiving signals comprising a plurality of sub-channelsoccupying different but mutually overlapping portions of frequencyspectrum, comprising: separating the signals into component signalscorresponding to the respective sub-channels; calculating interferenceestimates for at least some of said sub-channels, based on the componentsignals corresponding to reference ones of said sub-channels, saidreference sub-channels being one or more of (a) sub-channels bearing notransmitted data, (b) sub-channels having a fixed content which can besubtracted to obtain an interference estimate and (c) sub-channelshaving a content which can be estimated and subtracted to obtain aninterference estimate; subtracting the interference estimates from therespective component signals to produce adjusted component signals;wherein for any particular sub-channel the interference estimatetherefor is calculated as a weighted sum of interference content of thecomponent signals of some of said reference sub-channels (excluding theparticular sub-channel for which the interference estimate is to beused); wherein weights for said weighted sums are selected by measuringerrors in the particular sub-channel and adjusting the weights in asense such as to tend to reduce said error.
 2. A method according toclaim 1, for use with transmissions in which the signals in thesub-channels are allowed to assume only certain permitted values, themethod including estimating, from the component signal for a givensub-channel, which of the permitted values it represents, anddetermining the error of the sub-channel by subtracting said estimatedpermitted value from the adjusted component signal for that sub-channel.3. A method according to claim 2 in which the estimation of whichpermitted value a component signal represents is performed by asoft-decision decoder.
 4. A method according to claim 1 includingreceiving signals identifying idle sub-channels, the interferencecontent of the sub-channel being the component signal for thatsub-channel.
 5. A method according to claim 1 including receivingsignals identifying sub-channels containing known signals, anddetermining the interference content of the sub-channel by subtractingsaid known content from the component signal for that sub-channel.
 6. Amethod according to claim 1 for use with transmissions in which thesignals in the sub-channels are allowed to assume only certain permittedvalues, the method including estimating, for from the component signalfor a given sub-channel, which of the permitted values it represents,and determining the interference content of the sub-channel bysubtracting said estimated permitted value from the component signal forthat sub-channel.
 7. A receiver for signals comprising a plurality ofsub-channels occupying different but mutually overlapping portions offrequency spectrum, comprising: means for separating the signals intocomponent signals corresponding to the respective sub-channels; meansfor calculating interference estimates for at least some of saidsub-channels based on the component signals corresponding to referenceones of said sub-channels, said reference sub-channels being one or moreof (a) sub-channels bearing no transmitted data, (b) sub-channels havinga fixed content which can be subtracted to obtain an interferenceestimate and (c) sub-channels having a content which can be estimatedand subtracted to obtain an interference estimate; means for subtractingthe interference estimates from the respective component signals;wherein the calculating means is operable for any particular sub-channelto calculate interference estimate therefor as a weighted sum of theinterference content of the component signals of some of said referencesub-channels (excluding the particular sub-channel for which theinterference estimate is to be used); wherein the calculating means isoperable for any particular sub-channel to select weights for saidweighted sums by measuring errors in the particular sub-channel andadjusting the weights in a sense such as to tend to reduce said error.8. A receiver according to claim 7, for use with transmissions in whichthe signals in the sub-channels are allowed to assume only certainpermitted values, the calculating means includes means for estimating,from the component signal for a given sub-channel, which of thepermitted values it represents, and determining the error of thesub-channel by subtracting said estimated permitted value from theadjusted component signal for that sub-channel.
 9. A receiver accordingto claim 8 in which the permitted value estimating and error determiningmeans is a soft-decision decoder.
 10. A receiver according to claim 7including means receiving signals identifying idle sub-channels, theinterference content of the sub-channel being the component signal forthat sub-channel.
 11. A receiver according to claim 7 including meansreceiving signals identifying sub-channels containing known signals, andfor determining the interference content of the sub-channel bysubtracting said known content from the component signal for thatsub-channel.
 12. A receiver according to claim 7 for use withtransmissions in which the signals in the sub-channels are allowed toassume only certain permitted values, and including means forestimating, from the component signal for a given sub-channel, which ofthe permitted values it represents, and determining the interferencecontent of the sub-channel by subtracting said estimated permitted valuefrom the component signal for that sub-channel.
 13. A method ofreceiving signals comprising a plurality of sub-channels occupyingdifferent but mutually overlapping portions of frequency spectrum,comprising: separating the signals into component signals correspondingto the respective sub-channels; calculating interference estimates forat least some of said sub-channels based on the component signalscorresponding to reference ones of said sub-channels, said referencesub-channels being one or more of (a) sub-channels bearing notransmitted data, (b) sub-channels having a fixed content which can besubtracted to obtain an interference estimate and (c) sub-channelshaving a content which can be estimated and subtracted to obtain aninterference estimate; subtracting the interference estimates from therespective component signals to produce adjusted component signals,wherein for any particular sub-channel the interference estimatetherefor is calculated as a weighted sum of interference content of thecomponent signals of some of said reference sub-channels (excluding theparticular sub-channel for which the interference estimate is to beused); and selecting weights for said weighted sums by defining anassumed interfering signal, determining the sub-channel components thatwould be received if the received signals were to consist of the assumedinterfering signal alone, and adjusting the weights for said particularsub-channel such as to tend to reduce the magnitude of a differencebetween the sub-channel component in the respective sub-channel and theweighted sum of said determined sub-channel components due to theassumed interfering signal.
 14. A method according to claim 13 in whichthe assumed interfering signal is a white noise signal occupying one ormore defined portions of said frequency spectrum.
 15. A method accordingto claim 14 including receiving signals identifying one or more idlesub-channels, and defining the or each defined portion of spectrum aslying within a frequency range corresponding to an idle sub-channel orto a plurality of adjacent idle sub-channels.
 16. A method according toclaim 13 in which the weights are selected once.
 17. A method accordingto claim 13 in which the weights are reselected following a change inselection of the reference sub-channels.
 18. A method according to claim13 including receiving signals identifying idle sub-channels, theinterference content of the sub-channel being the component signal forthat sub-channel.
 19. A method according to claim 13 including receivingsignals identifying sub-channels containing known signals, anddetermining the interference content of the sub-channel by subtractingsaid known content from the component signal for that sub-channel.
 20. Amethod according to claim 13 for use with transmissions in which thesignals in the sub-channels are allowed to assume only certain permittedvalues, the method including estimating, for from the component signalfor a given sub-channel, which of the permitted values it represents,and determining the interference content of the sub-channel bysubtracting said estimated permitted value from the component signal forthat sub-channel.
 21. A receiver for signals comprising a plurality ofsub-channels occupying different but mutually overlapping portions offrequency spectrum, comprising: means for separating the signals intocomponent signals corresponding to the respective sub-channels; meansfor calculating interference estimates for at least some of saidsub-channels based on the component signals corresponding to referenceones of said sub-channels, said reference sub-channels being one or moreof (a) sub-channels bearing no transmitted data, (b) sub-channels havinga fixed content which can be subtracted to obtain an interferenceestimate and (c) sub-channels having a content which can be estimatedand subtracted to obtain an interference estimate; means for subtractingthe interference estimates from the respective component signals toproduce adjusted component signals; wherein the calculating means isoperable for any particular sub-channel to calculate the interferenceestimate therefor as a weighted sum of interference content of thecomponent signals of some of said reference sub-channels (excluding theparticular sub-channel for which the interference estimate is to beused); and means for selecting the weights for said weighted sums bydefining an assumed interfering signal, determining the sub-channelcomponents that would be received if the received signals were toconsist of the assumed interfering signal alone, and adjusting theweights for said particular sub-channel such as to tend to reduce themagnitude of a difference between the sub-channel component in therespective sub-channel and the weighted sum of said determinedsub-channel components due to the assumed interfering signal.
 22. Areceiver according to claim 21 in which the assumed interfering signalis a white noise signal occupying one or more defined portions of saidfrequency spectrum.
 23. A receiver according to claim 22 including meansfor receiving signals identifying one or more idle sub-channels, anddefining the or each defined portion of spectrum as lying within afrequency range corresponding to an idle sub-channel or to a pluralityof adjacent idle sub-channels.
 24. A receiver according to claim 21 inwhich the means for selecting the weights is operable to reselect theweights following a change in selection of the reference sub-channels.25. A receiver according to claim 21 including means receiving signalsidentifying idle sub-channels, the interference content of thesub-channel being the component signal for that sub-channel.
 26. Areceiver according to claim 21 including means receiving signalsidentifying sub-channels containing known signals, and for determiningthe interference content of the sub-channel by subtracting said knowncontent from the component signal for that sub-channel.
 27. A receiveraccording to claim 21 for use with transmissions in which the signals inthe sub-channels are allowed to assume only certain permitted values,and including means for estimating, for from the component signal for agiven sub-channel, which of the permitted values it represents, anddetermining the interference content of the sub-channel by subtractingsaid estimated permitted value from the component signal for thatsub-channel.
 28. A method of receiving signals comprising a plurality ofsub-channels occupying different but mutually overlapping portions offrequency spectrum, comprising: separating the signals into componentsignals corresponding to the respective sub-channels; calculatinginterference estimates for at least some of said sub-channels, based onthe component signals corresponding to reference ones of saidsub-channels; subtracting the interference estimates from the respectivecomponent signals; wherein the calculation comprises defining at leastone parameter of an assumed interfering signal; selecting a value forthe parameter(s) such as to tend to reduce a difference between anexpected interference in each reference sub-channel due to the assumedinterfering signal and interference content of the component signal forthat reference sub-channel; and calculating said interference estimatesas a function of the selected parameter(s); including receiving signalsidentifying sub-channels containing known signals, and determining theinterference content of the sub-channel by subtracting said knowncontent from the component signal for that sub-channel.
 29. A methodaccording to claim 28 for use with transmissions in which the signals inthe sub-channels are allowed to assume only certain permitted values,the method including estimating, for from the component signal for agiven sub-channel, which of the permitted values it represents, anddetermining the interference content of the sub-channel by subtractingsaid estimated permitted value from the component signal for thatsub-channel.
 30. A method of receiving signals comprising a plurality ofsub-channels occupying different but mutually overlapping portions offrequency spectrum, comprising: separating the signals into componentsignals corresponding to the respective sub-channels; calculatinginterference estimates for at least some of said sub-channels, based onthe component signals corresponding to reference ones of saidsub-channels; subtracting the interference estimates from the respectivecomponent signals; wherein the calculation comprises defining at leastone parameter of an assumed interfering signal; selecting a value forthe parameter(s) such as to tend to reduce a difference between anexpected interference in each reference sub-channel due to the assumedinterfering signal and interference content of the component signal forthat reference sub-channel; and calculating said interference estimatesas a function of the selected parameter(s); wherein, for use withtransmissions in which the signals in the sub-channels are allowed toassume only certain permitted values, the method includes estimating,for from the component signal for a given sub-channel, which of thepermitted values it represents, and determining the interference contentof the sub-channel by subtracting said estimated permitted value fromthe component signal for that sub-channel.
 31. A receiver for signalscomprising a plurality of sub-channels occupying different but mutuallyoverlapping portions of frequency spectrum, comprising: means forseparating the signals into component signals corresponding to therespective sub-channels; means for calculating interference estimatesfor at least some of said sub-channels, based on the component signalscorresponding to reference ones of said sub-channels; means forsubtracting the interference estimates from the respective componentsignals; wherein the calculating means is operable to define at leastone parameter of an assumed interfering signal; select a value for theparameter(s) such as to tend to reduce a difference between an expectedinterference in each reference sub-channel due to the assumedinterfering signal and interference content of the component signal forthat reference sub-channel; and calculate said interference estimates asa function of the selected parameter(s); the receiver further includingmeans receiving signals identifying sub-channels containing knownsignals, and for determining the interference content of the sub-channelby subtracting said known content from the component signal for thatsub-channel.
 32. A receiver according to claim 31 for use withtransmissions in which the signals in the sub-channels are allowed toassume only certain permitted values, and including means forestimating, for from the component signal for a given sub-channel, whichof the permitted values it represents, and determining the interferencecontent of the sub-channel by subtracting said estimated permitted valuefrom the component signal for that sub-channel.
 33. A receiver forsignals comprising a plurality of sub-channels occupying different butmutually overlapping portions of frequency spectrum, comprising: meansfor separating the signals into component signals corresponding to therespective sub-channels; means for calculating interference estimatesfor at least some of said sub-channels, based on the component signalscorresponding to reference ones of said sub-channels; means forsubtracting the interference estimates from the respective componentsignals; wherein the calculating means is operable to define at leastone parameter of an assumed interfering signal; select a value for theparameter(s) such as to tend to reduce a difference between an expectedinterference in each reference sub-channel due to the assumedinterfering signal and interference content of the component signal forthat reference sub-channel; and calculate said interference estimates asa function of the selected parameter(s); including, for use withtransmissions in which the signals in the sub-channels are allowed toassume only certain permitted values, means for estimating, for from thecomponent signal for a given sub-channel, which of the permitted valuesit represents, and determining the interference content of thesub-channel by subtracting said estimated permitted value from thecomponent signal for that sub-channel.